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DTSTART;TZID=America/New_York:20220512T160000
DTEND;TZID=America/New_York:20220512T170000
DTSTAMP:20260417T052653
CREATED:20220518T191802Z
LAST-MODIFIED:20220524T100552Z
UID:10000530-1652371200-1652374800@www.ieeetoronto.ca
SUMMARY:Visualization Techniques in Text Summarization of Online Transcripts – Students’ Research in ML and DL at Durham College
DESCRIPTION:Text summarization is a method for generating a summary of long texts by focusing on the sections that contain essential information while keeping the overall meaning intact. Its goal is to reduce the size of long documents\, which would be difficult and expensive to process manually. With the current explosion of data circulating in digital space\, particularly unstructured textual data\, there is a need to build tools that allow people to extract insights from it. Taking notes is a popular practice for many people employed in situations where it is essential to keep track of what is said\, such as during an online lecture. The art of note-taking does not entail taking down every single word stated but rather broad summaries of what is covered. Making succinct yet informative summaries is the key to successful note-taking. In this seminar\, we will be discussing how we have used visualization and data storytelling techniques in our project to make informed decisions. This project aims to address the difficulties of note-taking by building an application that produces notes based on the transcripts generated by the Automatic Speech Recognition (ASR) technology of the meeting platforms. We relied on visualization concepts for three major decisions that would define our project as a whole. These decisions are the choice of online meeting platform\, preference of text summarization model and the messaging platform choice. \nSpeaker(s): Manoj Varma Alluri\, Navaneeth Jawahar\, Sharath Kumar Prabhu\, Jeel Jani \nRegister: https://events.vtools.ieee.org/m/313207
URL:https://www.ieeetoronto.ca/event/visualization-techniques-in-text-summarization-of-online-transcripts-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/313207
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220512T140000
DTEND;TZID=America/New_York:20220512T150000
DTSTAMP:20260417T052653
CREATED:20220518T191856Z
LAST-MODIFIED:20220524T100552Z
UID:10000531-1652364000-1652367600@www.ieeetoronto.ca
SUMMARY:Fraud Data Analysis & Exploration using Interactive Tableau Dashboard – Students’ Research in ML and DL at Durham College
DESCRIPTION:Credit card fraud detection is an ever-growing problem in today’s financial market with a rapid increase in plastic card usage worldwide. According to the Nelson report\, by 2027\, financial service providers are expected to take a $40 billion hit globally in credit card losses\, a significant increase compared to previous years. Hence\, data-driven decisions can largely help in mitigating that risk. We chose this topic to deep dive into different aspects of Fraud Data Analysis & Exploration using Interactive Tableau Dashboard. Tableau dashboards can be very powerful in driving data-driven decisions. We created an interactive dashboard to help stakeholders or less technical people to drive insights\, understand data better\, and help in business decisions making. The interactive feature helps users to add filters as per their needs and understand the data in a way they want to analyze. Our dashboard is dynamic and would be updated when several filters are applied together. Multiple filters can be added to multiple charts at the same time. These charts are intuitive which makes even new users easily interact and understand the data. \nSpeaker(s): Priyanka Singh & Devy Ratnasari \nRegister: https://events.vtools.ieee.org/m/313201
URL:https://www.ieeetoronto.ca/event/fraud-data-analysis-exploration-using-interactive-tableau-dashboard-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/313201
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220510T110000
DTEND;TZID=America/New_York:20220510T120000
DTSTAMP:20260417T052653
CREATED:20220505T201243Z
LAST-MODIFIED:20220511T081818Z
UID:10000362-1652180400-1652184000@www.ieeetoronto.ca
SUMMARY:High Order Adaptive Mesh Refinement (AMR) for Divergence Constraint-Preserving Schemes (Prof. Dinshaw Balsara\, U. of Notre Dame)
DESCRIPTION:Join the IEEE Toronto Electromagnetics & Radiation Society Chapter for a talk on High Order Adaptive Mesh Refinement\, presented by Professor Dinshaw S. Balsara. \nAbstract: Adaptive mesh refinement (AMR) is the art of solving PDEs on a mesh hierarchy with increasing mesh refinement at each level of the hierarchy. Accurate treatment on AMR hierarchies requires accurate prolongation of the solution from a coarse mesh to a newly-defined finer mesh. For scalar variables\, suitably high order finite volume WENO methods can carry out such a prolongation. However\, classes of PDEs\, like computational electrodynamics (CED) and magnetohydrodynamics (MHD)\, require that vector fields preserve a divergence constraint. The primal variables in such schemes consist of normal components of the vector field that are collocated at the faces of the mesh. As a result\, the reconstruction and prolongation strategies for divergence constraint-preserving vector fields are necessarily more intricate. \nIn this talk\, we present a fourth order divergence constraint-preserving prolongation strategy that is analytically exact. Extension to higher orders using analytically exact methods is very challenging. To overcome that challenge\, a novel WENO-like reconstruction strategy is invented that matches the moments of the vector field in the faces where the vector field components are collocated. This approach is almost divergence constraint-preserving; so we call it WENO-ADP. To make it exactly divergence constraint-preserving\, a touch-up procedure is developed that is based on a constrained least squares (CLSQ) based method for restoring the divergence constraint up to machine accuracy. With the touch-up\, it is called WENO-ADPT. It is shown that refinement ratios of two and higher can be accommodated. An item of broader interest in this work is that we have also been able to invent very efficient finite volume WENO methods where the coefficients are very easily obtained and the multidimensional smoothness indicators can be expressed as perfect squares. We demonstrate that the divergence constraint-preserving strategy works at several high orders for divergence-free vector fields as well as vector fields where the divergence of the vector field has to match a charge density and its higher moments. We also show that our methods overcome the late time instability that has been known to plague adaptive computations in Computational Electrodynamics. \nCo-sponsored by: Center for Computational Science and Engineering\, University of Toronto \nSpeaker(s): Prof. D. S. Balsara\, \nRegister: https://events.vtools.ieee.org/m/312557 \nBiography: Dinshaw S. Balsara received the Ph.D. degree in computational physics and astrophysics from the University of Illinois at Urbana-Champaign\, Champaign\, IL\, USA\, in 1990. He is currently a Professor with the Department of Physics and the Department of Applied and Computational Mathematics and Statistics. He has developed computational algorithms and applications in the areas of interstellar medium\, turbulence\, star formation\, planet formation\, the physics of accretion disks\, compact objects\, and relativistic astrophysics. Many of the algorithms developed by him for higher order methods have seen extensive use and have been copiously cited. Dr. Balsara was the recipient of the 2014 Department of Energy Award of Excellence for significant contributions to the Stockpile Stewardship Program and the 2017 Global Initiative on Academic Networks Award from the Government of India. He serves the community as an Associate Editor of Journal of Computational Physics and Computational Astrophysics and Cosmology.
URL:https://www.ieeetoronto.ca/event/high-order-adaptive-mesh-refinement-amr-for-divergence-constraint-preserving-schemes-prof-dinshaw-balsara-u-of-notre-dame/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312557
CATEGORIES:Electromagnetics & Radiation
ORGANIZER;CN="Costas Sarris":MAILTO:costas.sarris@utoronto.ca
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220507T180000
DTEND;TZID=America/New_York:20220507T190000
DTSTAMP:20260417T052653
CREATED:20220505T200912Z
LAST-MODIFIED:20220507T074848Z
UID:10000361-1651946400-1651950000@www.ieeetoronto.ca
SUMMARY:Alert on Mask Detection System – Students Research in ML and DL at Durham College
DESCRIPTION:As a result of the fast development and spread of the COVID-19 pandemic throughout the world\, people’s everyday lives have been severely disrupted in recent times. One proposal for controlling the epidemic is to make individuals wear face masks in public. As a result\, we require face detection systems that are both automated and efficient for such enforcement. We propose a face mask identification model for static and real-time videos in this research\, and the pictures are classified as “with mask” or “without a mask.” The model uses a Kaggle dataset to train and test. The collected data set contains over 10\,000 images (considering 5\,000 with mask and similarly 5\,000 without) and has a 98 percent performance accuracy rate. The proposed model is computationally efficient and precise compared to Haar-Cascade & ANN. The application of this research are various\, including digitized scanning tool in schools\, hospitals\, banks\, airports\, and many other public or commercial locations. \nSpeaker(s): Henil Shah\, Neenu Markose \nRegister: https://events.vtools.ieee.org/m/312341
URL:https://www.ieeetoronto.ca/event/alert-on-mask-detection-system-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312341
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220506T183000
DTEND;TZID=America/New_York:20220506T203000
DTSTAMP:20260417T052653
CREATED:20220526T190240Z
LAST-MODIFIED:20220526T190240Z
UID:10000535-1651861800-1651869000@www.ieeetoronto.ca
SUMMARY:HUMBER IN PERSON COMPETITIVE PROGRAMMING WORKSHOPS
DESCRIPTION:Dr. Andrew Rudder will be teaching programming concepts with a focus on competitive programming. Various languages may be used. You should be familiar with any of the following programming languages Java\, C#\, C\, C++ or python. A basic knowledge of selection logic (such as if statements)\, loops and functions are sufficient. \nThis is a prerequisite for Humber IEEE Students attending IEEExtreme 16.0 in October 2022. Course continues depending on registration. Course is free. Available to any current Humber students. \nCourse will probably last until October 2022. Breaks for Humber Midterm exams\, final exams and reading weeks. \nLocation: Building F\, 205 Humber College Blvd\, Etobicoke\, Ontario\, Canada\, M9W5L7 \nRegister: https://events.vtools.ieee.org/m/312262
URL:https://www.ieeetoronto.ca/event/humber-in-person-competitive-programming-workshops/
LOCATION:Bldg: F\, 205 Humber College Blvd\, Etobicoke\, Ontario\, Canada\, M9W5L7\, Virtual: https://events.vtools.ieee.org/m/312262
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220506T180000
DTEND;TZID=America/New_York:20220506T190000
DTSTAMP:20260417T052653
CREATED:20220502T172656Z
LAST-MODIFIED:20220507T074847Z
UID:10000357-1651860000-1651863600@www.ieeetoronto.ca
SUMMARY:Cancer Level Detection System – Students Research in ML and DL at Durham College
DESCRIPTION:Cancer ranks as a leading cause of death and an important barrier to increasing life expectancy everywhere. According to available data\, lung cancer contributes the most to cancer deaths. Also\, according to available data\, those diagnosed early have a 50 percent chance of survival over those diagnosed with late-stage cancer. It means that early detection is paramount to the survival of a lung cancer patient\, leading to a reduction in the number of cancer deaths. We\, therefore\, evaluated six different machine learning algorithms to see which one performed optimally in accurately predicting the level of lung cancer development in a patient. We considered various parameters when choosing the dataset for this evaluation as the pathogenesis of lung cancer involves a combination of intrinsic factors and exposure to environmental carcinogens. We also considered varying the features in our data\, categorizing them under diagnostic risk factors (age\, gender\, alcohol use\, air pollution\, balanced diet\, obesity\, smoking\, passive smoker) and symptoms (fatigue\, weight loss\, shortness of breath\, swallowing difficulty\, frequent cold\, dry cough) and the inferences we drew from this indicated that those that have the symptom features prior to diagnosis had the highest chance of being diagnosed with a high level of cancer. The final results of our evaluation showed that the best levels of predictions on new data were achieved by optimized Random Forest\, KNN\, and SVM models. \nSpeakers: Rakesh Pattanayak\, Chisom Nnabuisi\, Dhruv Mistry\, Kar Chun Kan\, Shanuka Rathnayake \nRegister: https://events.vtools.ieee.org/m/312340
URL:https://www.ieeetoronto.ca/event/cancer-level-detection-system-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312340
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220505T183000
DTEND;TZID=America/New_York:20220505T203000
DTSTAMP:20260417T052653
CREATED:20220502T172442Z
LAST-MODIFIED:20220506T073312Z
UID:10000355-1651775400-1651782600@www.ieeetoronto.ca
SUMMARY:Humber Computer Hardware/Software Thursday evening
DESCRIPTION:Computer Hardware/Software course comparing Arduinos/ESP32/STM32/Raspberry Pi with simple to advanced programming in Arduino IDE in C++. Hardware includes Radios\, LED Displays\, LCD displays\, Servos\, I2c\, Clock chips\, Analog/Digital\, Touch Screens\, Flash Memory\, TSOP infrared\, TCP/IP\, Bluetooth and BLE Mesh. Do you want to learn beyond what Humber can offer? \nCourse is free. In-Person. Available to Humber Students on Thursday Evenings from 6:30 to 8:30. Also available Saturdays from 2-4. \nCourse is dependent on registrants and availability of lab space at that time. \nLocation: J232 Pending Approval\, Bldg: J\, 205 Humber College Blvd\,\nEtobicoke\, Ontario\, Canada\, M9W 5L7 \nRegister: https://events.vtools.ieee.org/m/312266
URL:https://www.ieeetoronto.ca/event/humber-computer-hardware-software-thursday-evening/
LOCATION:Room: J232 Pending Approval\, Bldg: J\, 205 Humber College Blvd\, Etobicoke\, Ontario\, Canada\, M9W 5L7\, Virtual: https://events.vtools.ieee.org/m/312266
ORGANIZER;CN="Humber College Inst of Tech & Advanced Learning":MAILTO:mdc_on_ca@hotmail.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220504T193000
DTEND;TZID=America/New_York:20220504T213000
DTSTAMP:20260417T052653
CREATED:20220505T200750Z
LAST-MODIFIED:20220505T200750Z
UID:10000359-1651692600-1651699800@www.ieeetoronto.ca
SUMMARY:Amateur Radio Morse Code Study
DESCRIPTION:Wednesday night Online Morse Code Study for the Canadian Amateur Radio certification exam. 2hrs/week \nCourse continues depending on registration. Course is free. Available to anyone. \nCourse will probably last until December 2022. Breaks for Humber Midterm exams\, final exams and reading weeks \nRegister: https://events.vtools.ieee.org/m/313669
URL:https://www.ieeetoronto.ca/event/amateur-radio-morse-code-study/
LOCATION:Etobicoke\, Ontario\, Canada\, M9V4A9\, Virtual: https://events.vtools.ieee.org/m/313669
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220504T160000
DTEND;TZID=America/New_York:20220504T173000
DTSTAMP:20260417T052653
CREATED:20220502T172244Z
LAST-MODIFIED:20220505T073259Z
UID:10000352-1651680000-1651685400@www.ieeetoronto.ca
SUMMARY:Conceiving Noise: Transformation from Disturbing Sounds to Informational Errors\, 1900-1955
DESCRIPTION:The Communications Group at the University of Toronto\, in collaboration with the IEEE Communications Society\, Toronto Chapter are happy to host the seminar titled “Conceiving Noise: Transformation from Disturbing Sounds to Informational Errors\, 1900-1955” given by Prof. Chen-Pang Yeang\, from the Institute for the History and Philosophy of Science and Technology\, University of Toronto. \nIn this talk\, Prof. Yeang examine the historical origin of the attempts to understand\, control\, and use noise at modern times.  Today\, the concept of noise is employed to characterize random fluctuations in general.  Before the twentieth century\, however\, noise only meant disturbing sounds.  In the 1900s-50s\, noise underwent a conceptual transformation from unwanted sounds that needed to be domesticated into a synonym for errors and deviations on all kinds of signals and information. Prof. Yeang argue that this transformation proceeded in four stages.  The rise of sound reproduction technologies—phonograph\, telephone\, and radio—in the 1900s-20s prompted engineers to tackle unwanted sounds as physical effects of media through quantitative representations and measurements.  Around the same time\, physicists developed a theory of Brownian motions for random fluctuations and applied it to electronic noise in thermionic tubes of telecommunication systems.  These technological and scientific backgrounds led to three distinct theoretical treatments of noise in the 1920s-30s: statistical physicists’ studies of Brownian fluctuations’ temporal evolution\, radio engineers’ spectral analysis of atmospheric disturbances\, and mathematicians’ measure-theoretic formulation.  Finally\, during and after World War II\, researchers working on the military projects of radar\, gunfire control\, and secret communications converted the interwar theoretical studies of noise into tools for statistical detection\, estimation\, prediction\, and information transmission.  In so doing\, they turned noise into an informational concept.  Since the grappling of noise involved multiple disciplines\, its history sheds light on the interactions between physics\, mathematics\, mechanical technology\, electrical engineering\, and information and data sciences in the twentieth century. \nSpeaker(s): Prof. Chen-Pang Yeang \nRegister: https://events.vtools.ieee.org/m/313075 \nBiography: Prof. Chen-Pang Yeang is an associate professor at the Institute for the History and Philosophy of Science and Technology\, University of Toronto.  Trained both in electrical engineering and the history of science and technology\, he does research and teaching in the history of physics\, electrical engineering\, information and computer science and technology in the 20th and 21st centuries.  He published Probing the Sky with Radio Waves: From Wireless Technology to the Development of Atmospheric Science (University of Chicago Press\, 2013).  He is completing a book on the history of noise.  In addition\, he is undertaking a research project that uses the material replication of Heinrich Hertz’s radio-wave experiment as a means of historical inquiry\, and another project on the grassroots innovation in information and computing technology in the US and China.
URL:https://www.ieeetoronto.ca/event/conceiving-noise-transformation-from-disturbing-sounds-to-informational-errors-1900-1955/
LOCATION:Virtual: https://events.vtools.ieee.org/m/313075
CATEGORIES:Communications
ORGANIZER;CN="IEEE Toronto Communications Chapter":MAILTO:Toronto_Chapter@comsoc.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220503T193000
DTEND;TZID=America/New_York:20220503T213000
DTSTAMP:20260417T052654
CREATED:20220502T171800Z
LAST-MODIFIED:20220504T073258Z
UID:10000348-1651606200-1651613400@www.ieeetoronto.ca
SUMMARY:Humber Amateur Radio certification study Tuesday online
DESCRIPTION:Tuesday night Online Study Group preparing for the Canadian Amateur Radio certification exam. 2hrs/week \nCourse based on the certification study guide from https://www.coaxpublications.ca/ord0001.php Purchase the book if you are serious about learning this. \nCourse continues depending on registration. Course is free. Available to anyone. \nCourse will probably last until December 2022. Breaks for Humber Midterm exams\, final exams and reading weeks \nEtobicoke\, Quebec\, Canada\, M9V4A9\, Virtual: https://events.vtools.ieee.org/m/312260
URL:https://www.ieeetoronto.ca/event/humber-amateur-radio-certification-study-tuesday-online/
LOCATION:Etobicoke\, Quebec\, Canada\, M9V4A9\, Virtual: https://events.vtools.ieee.org/m/312260
ORGANIZER;CN="Humber College Inst of Tech & Advanced Learning":MAILTO:mdc_on_ca@hotmail.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220503T180000
DTEND;TZID=America/New_York:20220503T190000
DTSTAMP:20260417T052654
CREATED:20220502T171646Z
LAST-MODIFIED:20220504T073258Z
UID:10000346-1651600800-1651604400@www.ieeetoronto.ca
SUMMARY:DDoS Detection System – Students Research in ML and DL at Durham College
DESCRIPTION:The research goal is to implement different machine learning algorithms to detect any DDoS (Distributed Denial of Service) attacks using the UNSW-NB15 dataset. We started by going through the data description and finding null values in our features. After that we dropped the ‘id’ column. \nWe have used the UNSW-15 dataset for AI-based DDOS detection systems. \nThe UNSW-15 dataset has a hybrid of the real modern normal and the contemporary synthesized attack activities of the network traffic. It contains different attacks\, including DoS\, worms\, Backdoors etc. The raw network packets of the UNSW-NB 15 datasets are created by the IXIA Perfect Storm tool in the Cyber Range Lab of the Australian Centre for Cyber Security (ACCS) for generating a hybrid of real modern normal activities and synthetic contemporary attack behaviours. We incorporated different feature selection methods for dropping insignificant features followed by the implementation of 6 classification algorithms\, namely Naive Bayes\, Random Forest\, Decision Tree\, KNN\, Logistic Regression and SVM. \nSpeaker(s): Minu Ahlawat\, Dwij Dua\, Megha Garg\, Taxil Savani \nRegister: https://events.vtools.ieee.org/m/312339
URL:https://www.ieeetoronto.ca/event/ddos-detection-system-students-research-in-ml-and-dl-at-durham-college/
LOCATION:toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312339
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220503T110000
DTEND;TZID=America/New_York:20220503T120000
DTSTAMP:20260417T052654
CREATED:20220502T172040Z
LAST-MODIFIED:20220504T073258Z
UID:10000350-1651575600-1651579200@www.ieeetoronto.ca
SUMMARY:Higher Order Globally Constraint-Preserving FVTD and DGTD Schemes for Time-Dependent Computational Electrodynamics (Prof. Dinshaw Balsara\, U. of Notre-Dame)
DESCRIPTION:Adaptive mesh refinement (AMR) is the art of solving PDEs on a mesh hierarchy with increasing mesh refinement at each level of the hierarchy. Accurate treatment on AMR hierarchies requires accurate prolongation of the solution from a coarse mesh to a newly-defined finer mesh. For scalar variables\, suitably high order finite volume WENO methods can carry out such a prolongation. However\, classes of PDEs\, like computational electrodynamics (CED) and magnetohydrodynamics (MHD)\, require that vector fields preserve a divergence constraint. The primal variables in such schemes consist of normal components of the vector field that are collocated at the faces of the mesh. As a result\, the reconstruction and prolongation strategies for divergence constraint-preserving vector fields are necessarily more intricate. \nIn this seminar\, we present a fourth order divergence constraint-preserving prolongation strategy that is analytically exact. Extension to higher orders using analytically exact methods is very challenging. To overcome that challenge\, a novel WENO-like reconstruction strategy is invented that matches the moments of the vector field in the faces where the vector field components are collocated. This approach is almost divergence constraint-preserving; so we call it WENO-ADP. To make it exactly divergence constraint-preserving\, a touch-up procedure is developed that is based on a constrained least squares (CLSQ) based method for restoring the divergence constraint up to machine accuracy. With the touch-up\, it is called WENO-ADPT. It is shown that refinement ratios of two and higher can be accommodated. An item of broader interest in this work is that we have also been able to invent very efficient finite volume WENO methods where the coefficients are very easily obtained and the multidimensional smoothness indicators can be expressed as perfect squares. We demonstrate that the divergence constraint-preserving strategy works at several high orders for divergence-free vector fields as well as vector fields where the divergence of the vector field has to match a charge density and its higher moments. We also show that our methods overcome the late time instability that has been known to plague adaptive computations in Computational Electrodynamics. \nCo-sponsored by: Center for Computational Science and Engineering (CCSE)\, University of Toronto \nSpeaker(s): Prof. Dinshaw Balsara\, \nRegister: https://events.vtools.ieee.org/m/312555 \nBiography: Dinshaw S. Balsara received the Ph.D. degree in computational physics and astrophysics from the University of Illinois at Urbana-Champaign\, Champaign\, IL\, USA\, in 1990. He is currently a Professor with the Department of Physics and the Department of Applied and Computational Mathematics and Statistics at the University of Notre Dame. He has developed computational algorithms and applications in the areas of interstellar medium\, turbulence\, star formation\, planet formation\, the physics of accretion disks\, compact objects\, and relativistic astrophysics. Many of the algorithms developed by him for higher order methods have seen extensive use and have been copiously cited.\,Dr. Balsara was the recipient of the 2014 Department of Energy Award of Excellence for significant contributions to the Stockpile Stewardship Program and the 2017 Global Initiative on Academic Networks Award from the Government of India. He serves the community as an Associate Editor of Journal of Computational Physics and Computational Astrophysics and Cosmology.
URL:https://www.ieeetoronto.ca/event/high-order-adaptive-mesh-refinement-amr-for-divergence-constraint-preserving-schemes-focus-on-mhd-and-ced-prof-dinshaw-balsara-university-of-notre-dame/
LOCATION:Virtual: https://events.vtools.ieee.org/m/312555
CATEGORIES:Electromagnetics & Radiation
ORGANIZER;CN="Costas Sarris":MAILTO:costas.sarris@utoronto.ca
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220501T180000
DTEND;TZID=America/New_York:20220501T190000
DTSTAMP:20260417T052654
CREATED:20220502T171452Z
LAST-MODIFIED:20220502T171549Z
UID:10000525-1651428000-1651431600@www.ieeetoronto.ca
SUMMARY:Sentiment Analysis on Twitter Data – Students Research in ML and DL at Durham College
DESCRIPTION:The rise of digitalization and the advent of social media and e-commerce have generated an abundance of data than before. Natural Language Processing (NLP) is a significant branch of artificial intelligence that helps the machine interpret human languages and perform the desired task by analyzing the semantics\, content\, and pattern. Sentiment analysis is the most common technique in Natural Language Processing used to determine the underlying sentiments of a text. This technique is currently in place for different Business Organizations to analyze their brand’s market value\, brand reputation\, and customer perception of new brand/new change. Businesses use social media channels to cater to their customer service\, and people use social media to express/share their wide range of opinions or experiences about a product/brand. These opinions and experiences reflect the real-time sentiments of a customer. Sentiment analysis will help businesses designing an effective marketing campaign\, better customer satisfaction\, boost sales\, help improve customer experience\, understand customer perception to change and the brand’s market reputation. The customer views expressed on Twitter\, Facebook\, and other online forums are forming the base of customer strategy for brands worldwide. Businesses are opting to shift their traditional customer feedback analysis method to text classification since people prefer to post the genuine reviews on the internet. Analyzing the underlying sentiments in the text will help the business to understand their customers’ voices and their brand reputation in the market in real-time. Sentiment analysis will help the businesses designing an effective marketing campaign\, better customer satisfaction\, boost sales\, help improve customer experience\, understand customer perception to change and the brand’s market reputation. Twitter sentiment analysis aims to classify text into positive/negative based on its underlying semantics. \nSpeaker(s): Akhil Mathew\, Anmol Wadera\, Deepan Ellenti Padmanabhan\, Saketh Vemula\, Sivaramakrishna Malakalapalli \nRegister: https://events.vtools.ieee.org/m/312338
URL:https://www.ieeetoronto.ca/event/sentiment-analysis-on-twitter-data-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312338
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220428T180000
DTEND;TZID=America/New_York:20220428T190000
DTSTAMP:20260417T052654
CREATED:20220425T202839Z
LAST-MODIFIED:20220429T070737Z
UID:10000524-1651168800-1651172400@www.ieeetoronto.ca
SUMMARY:Text Summarization of Transcripts from Online Meetings – Students Research in ML and DL at Durham College
DESCRIPTION:Text Summarization is a technique for generating a concise and precise summary of voluminous texts while focusing on the sections that convey useful information without losing the overall meaning. It aims to transform lengthy documents into shortened versions\, which could be difficult and costly to undertake if done manually. With the current explosion of data circulating in digital space\, primarily unstructured textual data\, there is a need to develop tools that allow people to get insights from them quickly. In situations where it is essential to keep track of what is being spoken\, such as during an online lecture\, taking notes is a popular activity used by many. The art of notetaking does not involve making notes of every single word that is spoken but comprehensive outlines of what is discussed. The key to good notetaking lies in making concise yet informative summaries. In this seminar\, we will be discussing how we have tried to address the difficulties of notetaking by building an application that produces notes based on transcripts generated by the Automatic Speech Recognition (ASR) technology of the meeting platforms. We experimented with six summarization models for this application\, including transformer-based models pre-trained on large corpora. The datasets used for this application are the transcripts dataset acquired from online meeting platforms and the Extreme Summarization (XSum) dataset. We evaluated the models using Rouge metrics (Rouge-1\, Rouge-2\, and Rouge-L) and selected the best-performing model as the final model. We have built a bot that utilizes Telegram’s API and shares the generated summaries via group chat with the users. \nSpeaker(s): Manoj Varma Alluri\, Navaneeth Jawahar\, Sharath Kumar Prabhu\, Jeel Jani\, Shravya Sandupata\nToronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312337
URL:https://www.ieeetoronto.ca/event/text-summarization-of-transcripts-from-online-meetings-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312337
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220428T173000
DTEND;TZID=America/New_York:20220428T190000
DTSTAMP:20260417T052654
CREATED:20220425T202739Z
LAST-MODIFIED:20220429T070736Z
UID:10000523-1651167000-1651172400@www.ieeetoronto.ca
SUMMARY:Electrification: Extraordinary Opportunities\, Extreme Challenges
DESCRIPTION:Despite a head start over 100 years ago\, Electrification is only receiving widespread interest recently.\nSee attached poster for more details. \n\nThis is a hybrid meeting with in-person event shared on the web. http://meet.google.com/xdn-kpji-eyk \nSIRC Building is on the corner of Conlin Road and Simcoe Rd North. There is parking in the rear of the Building. \nCo-sponsored by: Ontario Tech University \nSpeaker(s): Rick Szymczyk P.Eng.\, MBA\, \nLocation:\n2060\, Bldg: Software and Informatics Research Centre\, Ontario Tech University\,\n2000 Simcoe Street North\, Oshawa\, Ontario\, Canada\, L1G 0C5
URL:https://www.ieeetoronto.ca/event/electrification-extraordinary-opportunities-extreme-challenges/
LOCATION:Room: 2060\, Bldg: Software and Informatics Research Centre\, Ontario Tech University\, 2000 Simcoe Street North\, Oshawa\, Ontario\, Canada\, L1G 0C5
CATEGORIES:Life Members
ORGANIZER;CN="Vijay Sood":MAILTO:vijay.sood@ontariotechu.ca
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220427T180000
DTEND;TZID=America/New_York:20220427T190000
DTSTAMP:20260417T052654
CREATED:20220425T202533Z
LAST-MODIFIED:20220429T070736Z
UID:10000522-1651082400-1651086000@www.ieeetoronto.ca
SUMMARY:Credit Card Fraud Detection – Students Research in ML and DL at Durham College
DESCRIPTION:With the new trend of Online Shopping and Online Platforms for transactions\, the number of Credit Card based transactions increased tremendously. However\, there have been a lot of cases where illegal use of Debit/Credit Cards for making Fraudulent Transactions. Credit card companies have been paying a lot of attention to providing the best service for their customers by having process enhancements and pro-actively looking into transactions before making them through. Global financial losses related to payment cards are estimated to reach $34.66 billion in 2022\, according to The Nilson Report\, a newsletter that tracks the payment industry. Related to the negative impacts of credit card fraud activities\, and financial and product losses\, it’s easy for merchants and users to feel victimized and helpless. Machine Learning Models can work well in detecting such Fraudulent actions when they are trained on a large quantity of historical data and then fine-tuned depending on validation and evaluation metrics. \nSpeaker(s): Priyanka Singh\, Devy Ratnasari\, Gopika Shaji\, Oluwole Ayodele\, Saurav Bisht\,\nToronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312336
URL:https://www.ieeetoronto.ca/event/credit-card-fraud-detection-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312336
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220426T180000
DTEND;TZID=America/New_York:20220426T190000
DTSTAMP:20260417T052654
CREATED:20220425T202413Z
LAST-MODIFIED:20220426T234759Z
UID:10000521-1650996000-1650999600@www.ieeetoronto.ca
SUMMARY:Fake News Detection – Students Research in ML and DL at Durham College
DESCRIPTION:The term “fake news” was pretty much unknown and unpopular a few decades ago\, but it has emerged as a massive monster in the digital era of social media. Fake news is spreading like wildfire these days\, and people share it without confirming it. Often\, it is to promote or enforce specific views\, and it is carried out through political agendas. Fake news refers to news that may or may not be correct and is widely disseminated via social media and other internet platforms. \nIn this digital age\, it is not easy to tackle the spread of fake news\, where thousands of information-sharing sites via fake news or misinformation can be shared. It has become a greater issue as AI advances\, bringing with it artificial bots that may be used to create and propagate fake news. The problem is critical because many individuals believe anything they read on the internet\, and those who are inexperienced or new to digital technologies are vulnerable to being misled. Fraud is another issue that can arise as a result of spam or harmful emails and communications.\nFake news has grown in popularity and spread as a result of recent political events. Humans are inconsistent\, if not outright terrible detectors of fake news\, as evidenced by the pervasive effects of the widespread onset of fake news. As a result\, efforts have been made to automate detecting fake news. The most prominent of these attempts are “blacklists” of unreliable sources and authors. While these technologies are useful we need to account for more complex instances when trusted sources and authors leak fake news in order to provide a complete end-to-end solution. As a result\, the goal of this project was to develop a tool that used machine learning and natural language processing techniques to recognize the language patterns that distinguish fake and true news. The outcomes of this project show that machine learning can be effective in this situation. We developed a model that detects a variety of intuitive indicators of real and fake news and an application to aid in the visual representation of the classification decision. We aim to give users the ability to classify news as fake or real and verify the website legitimacy that published it. \nSpeaker(s): Roshna Babu\, Abraham Mathew\, Neha Joseph\nToronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312334
URL:https://www.ieeetoronto.ca/event/fake-news-detection-students-research-in-ml-and-dl-at-durham-college/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/312334
CATEGORIES:Magnetics,Women in Engineering
ORGANIZER;CN="Reza Dibaj":MAILTO:reza.dibaj@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220421T161000
DTEND;TZID=America/New_York:20220421T170000
DTSTAMP:20260417T052654
CREATED:20220330T181903Z
LAST-MODIFIED:20220421T231238Z
UID:10000514-1650557400-1650560400@www.ieeetoronto.ca
SUMMARY:Wideband Digital-to-Analog Converters for mmWave Transmitter
DESCRIPTION:Over the past ten years\, the data rate of cellular communication networks has increased by 100x. The next-generation software-defined-radio based wireless transmission in mmWave bands demands multi-GHz bandwidth digital-to-analog conversion with medium to high resolution (e.g.\, 14-16 bit) and sampling rates beyond 10GS/s. The rate of bandwidth increase and the required improvements in energy efficiency have exceeded the benefits of CMOS process scaling alone. There are compelling needs for novel architecture and circuit design techniques. In this talk\, I will review recent development and present emerging parallel-path DAC architectures for extending the bandwidth with higher power and area efficiency than conventional interleaving designs. I will discuss the practical challenges along with several key analog design techniques. I will conclude with some future directions. At the end of the talk\, I will briefly introduce some other research activities in my group\, such as low power bioelectronics\, neural interfacing and modulation circuits\, and machine-learning accelerators. \nSpeaker(s): Dr. Xilin Liu \nVirtual: https://events.vtools.ieee.org/m/309574 \nBiography: Dr. Xilin Liu (Senior Member\, IEEE) is currently an Assistant Professor at the University of Toronto. He obtained his Ph.D. degree from the University of Pennsylvania. Before joining the University of Toronto in 2021\, he held industrial positions at Qualcomm Inc.\, where he conducted R&D of high-performance mixed-signal circuits for cellular communication. He led and contributed to the IPs that have been integrated into products in high-volume production\, including the industry’s first 5G chipset. He was a visiting scholar at Princeton University in 2014. He has co-authored two books along with over 30 peer-reviewed articles. He was the first author of the papers that have received the Best Student Paper Award at the 2017 ISCAS\, the Best Paper Award at the 2015 BioCAS\, the Best Track Award at the 2014 ISCAS\, and the student research preview (SRP) award at 2014 ISSCC. He also received the SSCS predoctoral achievement award at the 2016 ISSCC.
URL:https://www.ieeetoronto.ca/event/wideband-digital-to-analog-converters-for-mmwave-transmitter/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/309574
CATEGORIES:Solid-State Circuits
ORGANIZER;CN="Dustin Dunwell":MAILTO:dustin.dunwell@gmail.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220421T160000
DTEND;TZID=America/New_York:20220421T170000
DTSTAMP:20260417T052654
CREATED:20220425T202249Z
LAST-MODIFIED:20220425T202249Z
UID:10000519-1650556800-1650560400@www.ieeetoronto.ca
SUMMARY:Distributed Phased Arrays: Challenges and Recent Progress
DESCRIPTION:There has been significant research devoted to the development of distributed microwave wireless systems in recent years. The progression from large\, single-platform wireless systems to collections of smaller\, coordinated systems on separate platforms enables significant benefits for radar\, remote sensing\, communications\, and other applications. The ultimate level of coordination between platforms is at the wavelength level\, where separate platforms operate as a coherent distributed system. Wireless coherent distributed systems operate in essence as distributed phased arrays\, and the signal gains that can be achieved scale proportionally to the number of transmitters squared multiplied by the number of receivers\, providing potentially dramatic increases in wireless system capabilities. Distributed array coordination requires accurate control of the relative electrical states of the nodes. Generally\, such control entails wireless frequency synchronization\, phase calibration\, and time alignment\, but for remote sensing operations\, phase control also requires high-accuracy knowledge of the relative positions of the nodes in the array to support beamforming. \nThis lecture presents an overview of the challenges involved in distributed phased array coordination\, and describes recent progress on microwave technologies that address these challenges. Requirements for achieving distributed phase coherence at microwave frequencies are discussed\, including the impact of component non-idealities such as oscillator drift on beamforming performance. Architectures for enabling distributed beamforming are reviewed\, along with the relative challenges between transmit and receive beamforming. Microwave and millimeter-wave technologies enabling wireless phase-coherent synchronization are discussed\, focusing on technologies for high-accuracy internode ranging\, wireless frequency transfer\, and high-accuracy time alignment. The lecture concludes with a discussion of open challenges in distributed phased arrays\, and where microwave technologies may play a role. \nSpeaker(s): Prof. Jeffrey Nanzer \nRegister: https://events.vtools.ieee.org/m/311733 \nBiography: \n \nJeffrey Nanzer (S’02-M’08-SM’14) received the B.S. degree in electrical engineering and computer engineering from Michigan State University\, East Lansing\, MI\, USA\, in 2003\, and the M.S. and Ph.D. degrees in electrical engineering from The University of Texas at Austin\, Austin\, TX\, USA\, in 2005 and 2008\, respectively. From 2008 to 2009\, he was a Postdoctoral Fellow with Applied Research Laboratories\, The University of Texas at Austin\, where he was involved in designing electrically small HF antennas and communication systems. From 2009 to 2016\, he was with The Johns Hopkins University Applied Physics Laboratory\, Laurel\, MD\, USA\, where he created and led the Advanced Microwave and Millimeter-Wave Technology Section. In 2016\, he joined the Department of Electrical and Computer Engineering\, Michigan State University\, where he is currently the Dennis P. Nyquist Associate Professor. He has authored or co-authored more than 150 refereed journal and conference papers\, authored the book Microwave and Millimeter-Wave Remote Sensing for Security Applications (Artech House\, 2012)\, and co-authored chapters in the books Wireless Transceiver Circuits (Taylor and Francis\, 2015) and Short-Range Micro-Motion Sensing: Hardware\, signal processing and machine learning (IET\, 2019). His current research interests include distributed arrays\, radar and remote sensing\, antennas\, electromagnetics\, and microwave photonics. \nDr. Nanzer was a founding member and the First Treasurer of the IEEE APS/MTT-S Central Texas Chapter. He is also a member of the IEEE Antennas and Propagation Society Education Committee and the USNC/URSI Commission B. He was a recipient of the Outstanding Young Engineer Award from the IEEE Microwave Theory and Techniques Society in 2019\, the DARPA Director’s Fellowship in 2019\, the National Science Foundation (NSF) CAREER Award in 2018\, the DARPA Young Faculty Award in 2017\, and the JHU/APL Outstanding Professional Book Award in 2012. He has served as the Vice-Chair for the IEEE Antenna Standards Committee from 2013 to 2015 and the Chair of the Microwave Systems Technical Committee (MTT-16) of the IEEE Microwave Theory and Techniques Society from 2016 to 2018. He is also an Associate Editor of the IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION.
URL:https://www.ieeetoronto.ca/event/distributed-phased-arrays-challenges-and-recent-progress/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/311733
CATEGORIES:Electromagnetics & Radiation
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220414T200000
DTEND;TZID=America/New_York:20220414T210000
DTSTAMP:20260417T052654
CREATED:20220330T181712Z
LAST-MODIFIED:20220414T223257Z
UID:10000512-1649966400-1649970000@www.ieeetoronto.ca
SUMMARY:Intelligent and Secure Integration of Electric Vehicles into the Smart Grid
DESCRIPTION:The transition to electric vehicles (EVs) is gaining momentum around the world and the major drivers for this acceleration are the rising awareness by the public for maintaining a clean environment\, reducing pollutant emissions\, breaking dependencies on oil\, as well as tapping into cleaner sources of energies. EVs acceptance however is hindered by several challenges; among them is their shorter driving range\, slower charging rates\, and the ubiquitous availability of charging locations\, collectively contributing to higher anxieties for EVs drivers. To mitigate this anxiety\, a naïve approach is to expand the charging network\, while an unplanned expansion may challenge the generation\, transmission and distribution sector of the grid along with being a potential cyber-physical attack platform. As a consequence\, to attain a graceful EV penetration for curtailing GHG emission\, along with the socioeconomic initiatives\, an extensive research is required\, especially to mitigate the range anxiety and ameliorate the load congestion on the grid. Fortunately\, the IoT enabled charging ecosystem (i.e.\, EVs\, charging stations\, the grid etc.) enables smart and informed charging schemes to exploit the benefit of different distributed energy sources (e.g.\, renewable energy based standalone chargers\, vehicle to grid or vehicle to vehicle energy transfer technology\, etc.) to minimize the load burden of the grid. But\, on the other hand\, this IoT enabled charging ecosystem unveils a new cyber-physical attack surface and hence\, new challenges also need to be addressed to make this charging ecosystem secure as well. \nVirtual: https://events.vtools.ieee.org/m/309875 \nSpeaker: Dr. Mohammad Ekramul Kabir \nBiography: Dr. Mohammad Ekramul Kabir is currently working as a Horizon postdoctoral research fellow in CIISE at Concordia University\, Montreal\, Canada. He obtained his PhD on Information and Systems Engineering from Concordia University in May 2021. He has received the B.Sc. and M.S. degree in Applied Physics\, Electronics and Communication engineering from University of Dhaka\, Bangladesh. His research interests include green\, smart\, and secure charging of electric vehicle\, cloud/edge computing security and applications of artificial intelligence. He is a coauthor of a number of peer-reviewed journal and conference papers. He also serves/served as a reviewer for IEEE Transactions on Transportation Electrification\, IEEE Transactions on Vehicular Technology\, IEEE Transactions on Mobile Computing\, IEEE Transactions on Network and Service Management\, IEEE Intelligent Transportation Systems Magazine\, IEEE PES General Meeting\, etc.
URL:https://www.ieeetoronto.ca/event/intelligent-and-secure-integration-of-electric-vehicles-into-the-smart-grid/
LOCATION:Virtual: https://events.vtools.ieee.org/m/309875
CATEGORIES:Vehicular Technology
ORGANIZER;CN="Lian Zhao":MAILTO:l5zhao@ryerson.ca
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220413T150000
DTEND;TZID=America/New_York:20220413T160000
DTSTAMP:20260417T052654
CREATED:20220412T171848Z
LAST-MODIFIED:20220413T223446Z
UID:10000517-1649862000-1649865600@www.ieeetoronto.ca
SUMMARY:Integrated Solar-Pannel Antennas by Prof. Reyhan Baktur
DESCRIPTION:Please join us for an upcoming talk on Apr 13\, 3-4 pm (Eastern Time) by Prof. Reyhan Baktur titled “Integrated Solar-Pannel Antennas\,” as part of the 2021-2022 IEEE AP-S seminar series. \nAbstract: \nConformal Integration of antennas with solar panels has wide applications\, from small spacecraft\, Mars rovers\, to self-powered wireless sensors. It is particularly beneficial when the surface real estate is a major challenge\, such as a CubeSat. A strategic integration not only reduces the development cost\, promotes a robust communication link\, but also increases the mission capacity by allowing more science instruments to be mounted on the CubeSat. \nThis lecture covers different conformal antenna designs for solar panel integration\, from UHF to Ka band. It includes antennas integrated under solar cells\, around solar cells\, and optically transparent antennas integrated on top of solar cells. It also covers low gain and high gain design. The high gain design mainly focuses on reflectarray antenna\, which may be beneficial to those who wishes to study the subject. \nAs these antennas are integrated with solar panel\, a unique and complex subsystem\, effects of solar cells on the antenna and vice versa need to be analyzed and quantified. The lecture presents analysis of a typical space-certified solar cell\, extracted model\, experimental set-up to quantify the interaction between solar cells and the integrated antennas. \nAbout Speaker: \n \nDr. Reyhan Baktur is an associate professor at the department of Electrical and Computer Engineering (ECE)\, Utah State University (USU). Her research interests include antennas and microwave engineering with a focus on antenna design for CubeSats; optically transparent antennas; multifunctional integrated antennas\, sensors\, and microwave circuits. She is affiliated with the Center for Space Engineering at USU\, the Space Dynamics Laboratory (the university affiliated research center)\, and collaborates with NASA Goddard Space Flight Center. Dr. Baktur is an AdCom member of IEEE Antennas and Propagation Society\, and is active in US National Committee of the International Union of Radio Science\, serving as the vice chair for commission B\, and the inaugural chair for the Women in Radio Science. She is passionate and committed to electromagnetic education and student recruiting by introducing CubeSat projects in undergraduate classrooms. She is the recipient of the IEEE Antennas and Propagation Society’s (APS) the Donald G. Dudley Jr. Undergraduate Teaching Award in 2013 and has been actively serving IEEE APS student paper competition and student design contest. Dr. Baktur’s lectures will focus on CubeSat Development Basics\, Link Budget Analysis and Development\, Antenna Designs for CubeSats and Small Satellites\, Transparent Antennas\, and Class Projects for Electromagnetic Courses
URL:https://www.ieeetoronto.ca/event/integrated-solar-pannel-antennas-by-prof-reyhan-baktur/
LOCATION:Toronto\, Ontario\, Canada
CATEGORIES:Electromagnetics & Radiation
ORGANIZER;CN="University of Toronto AP-S":MAILTO:pz.naseri@gmail.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220408T100000
DTEND;TZID=America/New_York:20220408T113000
DTSTAMP:20260417T052654
CREATED:20220330T182106Z
LAST-MODIFIED:20220408T215623Z
UID:10000515-1649412000-1649417400@www.ieeetoronto.ca
SUMMARY:Overview of Factory Automation Market in Canada
DESCRIPTION:The goal of the session is to present a summary of the automation industry in Canada with a focus on factory automation. The following topics would be covered:\n– Active Industries\n– Market Structure\n– Key Players\n– Future Trends\n– Automation Jobs\n– Required Skills\n– Challenges \nSpeaker(s): Shahram Fahimi \nVirtual: https://events.vtools.ieee.org/m/309678 \nBiography: Shahram Fahimi is the Automation Manager of the Life Science group in SNC-Lavalin. He has over 20 years of experience in the automation industry with a focus on Factory and Process Automation. Shahram has contributed to many exciting automation projects such as the first battery line for Tesla in California using Trak technology. He has been graduated from Sharif University of Technology in 1998 with a Bachelor of Computer Engineering.
URL:https://www.ieeetoronto.ca/event/overview-of-factory-automation-market-in-canada/
LOCATION:Virtual: https://events.vtools.ieee.org/m/309678
CATEGORIES:Instrumentation & Measurement
ORGANIZER;CN="Saba Sedghizadeh":MAILTO:s.sedghizadeh.CA@ieee.org
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220329T190000
DTEND;TZID=America/New_York:20220329T201500
DTSTAMP:20260417T052654
CREATED:20220330T181530Z
LAST-MODIFIED:20220330T181530Z
UID:10000510-1648580400-1648584900@www.ieeetoronto.ca
SUMMARY:Integration of Terrestrial Networks and Extreme Environments: Challenges and Capabilities
DESCRIPTION:The IEEE ComSoc New York Chapter a long with the IEEE ComSoc Toronto chapter are organizing a series of technical seminars. We invite researchers and professionals to share their latest work on a variety of topics in communications and related areas. This time\, we have the great pleasure to invite Prof. Mehdi Rahmati from Cleveland State University to talk about the integration of terrestrial networks and extreme environments. \nAgenda: \n06:45 PM – 07:00 PM Connecting to the ZOOM meeting\n07:00 PM – 07:05 PM Welcoming & IEEE ComSoc Membership Promotion\n07:05 PM – 07:10 PM Speaker Introduction\n07:10 PM – 07:55 PM Presentation\n07:55 PM – 08:10 PM Questions and Answers\n08:10 PM – 08:15 PM Closing Remarks \nVirtual: https://events.vtools.ieee.org/m/308601
URL:https://www.ieeetoronto.ca/event/integration-of-terrestrial-networks-and-extreme-environments-challenges-and-capabilities/
LOCATION:Virtual: https://events.vtools.ieee.org/m/308601
CATEGORIES:Communications
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220310T160000
DTEND;TZID=America/New_York:20220310T171500
DTSTAMP:20260417T052654
CREATED:20220307T181656Z
LAST-MODIFIED:20220307T181656Z
UID:10000506-1646928000-1646932500@www.ieeetoronto.ca
SUMMARY:Women in Leadership
DESCRIPTION:“Women in Leadership”\, a collaboration between IEEE Toronto Section\, Gybo Robotics\, and Humber College. \nCo-sponsored by: Humber College \nSpeaker(s): Dr. Azadeh Yadollahi \nVirtual: https://events.vtools.ieee.org/m/306228
URL:https://www.ieeetoronto.ca/event/women-in-leadership/
LOCATION:Virtual: https://events.vtools.ieee.org/m/306228
CATEGORIES:Instrumentation & Measurement,Women in Engineering
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220306T123000
DTEND;TZID=America/New_York:20220306T133000
DTSTAMP:20260417T052654
CREATED:20220307T181828Z
LAST-MODIFIED:20220307T181828Z
UID:10000508-1646569800-1646573400@www.ieeetoronto.ca
SUMMARY:Machine Learning and TensorFlow: An Introduction and Overview
DESCRIPTION:The workshop host will present an overview of the essential structure of machine learning along with an example using TensorFlow Hub. We will aim to take a practical approach to this complex subject for the purposes of gaining insight into some of the theory behind the code. Over the course of this workshop we will aim to cover: \n– A general overview of machine learning (ML) and its current context in artificial intelligence.\n– Useful mathematics for gaining an intuitive understanding of some basic processes in ML.\n– A discussion of possible projects that could involve ML along with example code in Python programming language. \nPrior exposure to Python/C programming and calculus will be helpful but isn’t required. \nSpeaker(s): John Hooper \nVirtual: https://events.vtools.ieee.org/m/306166
URL:https://www.ieeetoronto.ca/event/machine-learning-and-tensorflow-an-introduction-and-overview/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/306166
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220303T190000
DTEND;TZID=America/New_York:20220303T200000
DTSTAMP:20260417T052654
CREATED:20220223T200602Z
LAST-MODIFIED:20220303T172041Z
UID:10000504-1646334000-1646337600@www.ieeetoronto.ca
SUMMARY:Computation Offloading and Task Scheduling at Network Edge
DESCRIPTION:In the 5G era\, wireless networks are anticipated to provide connectivity for massive mobile devices and to enable a variety of innovative applications\, which generate enormous computing service demands with diverse and stringent Quality of Service requirements. To support the emerging computing service demands\, Mobile Edge Computing (MEC)\, as a cutting-edge technology in 5G\, utilizes computing resources on the network edge to provide computing services for mobile devices within a radio access network. In this talk\, we will investigate computing resource management for MEC to satisfy diverse computing requirements in wireless networks. We will introduce three computation offloading and task scheduling schemes tailored for supporting representative use cases and network scenarios in 5G\, including autonomous driving\, Unmanned Aerial Vehicle (UAV) assisted networks\, and highly dense vehicular networks. Machine learning algorithms are applied to facilitate low-latency and reliable computing services in complex and dynamic network environments. \nSpeaker(s): Mushu Li \nBiography: Dr. Mushu Li received the Ph.D. degree from the University of Waterloo\, ON\, Canada\, in 2021\, and the M.A.Sc. degree from Ryerson University\, Toronto\, ON\, Canada\, in 2017. She is currently a Postdoctoral Fellow with the Department of Electrical and Computer Engineering\, University of Waterloo.  Dr. Li was a recipient of the NSERC Canada Graduate Scholarship (2018-2021) and Ontario Graduate Scholarship in 2015 and 2016\, respectively. Her research interests include Internet of vehicles\, resource management\, multi-access edge computing\, and reinforcement learning. She has authored/co-authored over 20 technical papers. She serves/served as a reviewer for IEEE Journals on Selected Areas in Communications (JSAC)\, IEEE Transactions on Communications\, IEEE Transactions on Vehicular Technologies\, etc. \nVirtual: https://events.vtools.ieee.org/m/305769
URL:https://www.ieeetoronto.ca/event/computation-offloading-and-task-scheduling-at-network-edge/
LOCATION:Virtual: https://events.vtools.ieee.org/m/305769
CATEGORIES:Vehicular Technology
ORGANIZER;CN="Lian Zhao":MAILTO:l5zhao@ryerson.ca
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220225T160000
DTEND;TZID=America/New_York:20220225T173000
DTSTAMP:20260417T052654
CREATED:20220209T161711Z
LAST-MODIFIED:20220225T163321Z
UID:10000502-1645804800-1645810200@www.ieeetoronto.ca
SUMMARY:Fast Solvers for Electromagnetics-Based Analysis and Design of Integrated Circuits and Systems
DESCRIPTION:The design of advanced integrated circuits and microsystems from zero to terahertz frequencies calls for fast and accurate electromagnetics-based modeling and simulation. The sheer complexity and high design cost associated with the integrated circuits and microsystems prevent one from designing them based on hand calculation\, approximation\, intuition\, or trial and error. The move towards higher frequencies and heterogeneous technologies stresses the need even more. \nHowever\, the analysis and design of integrated circuits (ICs) and microsystems impose many unique challenges on electromagnetic analysis such as exponentially increased problem size and extremely multiscaled system spanning from nano- to centi-meter scales. These challenges become new driving forces of the advancement of Computational Electromagnetics (CEM) in recent years\, since past techniques do not address them well. \nIn this talk\, recent advances in fast direct solvers of O(N) (optimal) complexity will be presented\, including both direct PDE and IE solvers\, for addressing the ultra large problem size encountered in the IC design problems. In these solvers\, the underlying dense or sparse system matrix is directly inverted or factorized in O(N) complexity. To show how these solvers work\, a series of new accuracy controlled fast matrix arithmetic will be elaborated including the representation of a dense matrix of O(N2) elements using O(N) parameters with controlled accuracy\, subsequent matrix-matrix multiplication\, matrix factorization\, and inversion performed in O(N) complexity with directly controlled accuracy. The application of these fast algorithms to the design and analysis of industry product-level integrated circuits and systems will be presented. Comparisons with direct and iterative solvers in the past will be made\, which demonstrate the clear advantages of the new O(N) direct solvers. \nCo-sponsored by: Center for Computational Science and Engineering (CCSE)\, Faculty of Applied Science and Engineering\, University of Toronto \nSpeaker(s): Dan Jiao \nBiography: \n \nDan Jiao received the Ph.D. degree in electrical engineering from the University of Illinois at Urbana-Champaign\, Urbana\, IL\, USA\, in 2001. She then joined the Technology Computer-Aided Design (CAD) Division\, Intel Corporation\, until September 2005\, where she was a Senior CAD Engineer\, Staff Engineer\, and Senior Staff Engineer. In September 2005\, she joined Purdue University\, West Lafayette\, IN\, USA\, as an Assistant Professor with the School of Electrical and Computer Engineering. She is currently a Professor with Purdue University. She has authored 3 book chapters and over 300 papers in refereed journals and international conferences. Her current research interests include computational electromagnetics; high-frequency digital\, analog\, mixed-signal\, and RF integrated circuit (IC) design and analysis; high-performance very large scale integration (VLSI) CAD; modeling of microscale and nanoscale circuits; applied electromagnetics; fast and high-capacity numerical methods; fast time-domain analysis\, scattering and antenna analysis; RF\, microwave\, and millimeter-wave circuits; wireless communication; and bioelectromagnetics. \nDr. Jiao has served as a reviewer for many IEEE publications and conferences. She is an associate editor for the IEEE Transactions on Components\, Packaging\, and Manufacturing Technology. She was the recipient of the 2013 S. A. Schelkunoff Prize Paper Award of the IEEE Antennas and Propagation Society\, which recognizes the Best Paper published in the IEEE Transactions on Antennas and Propagation during the previous year. She has been named a University Faculty Scholar by Purdue University since 2013. She was among the 85 engineers selected throughout the nation for the National Academy of Engineerings 2011 U.S. Frontiers of Engineering Symposium. She was the recipient of the 2010 Ruth and Joel Spira Outstanding Teaching Award\, the 2008 National Science Foundation (NSF) CAREER Award\, the 2006 Jack and Cathie Kozik Faculty Start Up Award (which recognizes an outstanding new faculty member of the School of Electrical and Computer Engineering\, Purdue University)\, a 2006 Office of Naval Research (ONR) Award under the Young Investigator Program\, the 2004 Best Paper Award presented at the Intel Corporation’s annual corporate-wide technology conference (Design and Test Technology Conference) for her work on generic broadband model of high-speed circuits\, the 2003 Intel Corporation Logic Technology Development (LTD) Divisional Achievement Award\, the Intel Corporation Technology CAD Divisional Achievement Award\, the 2002 Intel Corporation Components Research Award\, the Intel Hero Award (Intel-wide she was the tenth recipient)\, the Intel Corporation LTD Team Quality Award\, and the 2000 Raj Mittra Outstanding Research Award presented by the University of Illinois at Urbana–Champaign. \nRegister: https://events.vtools.ieee.org/m/303190
URL:https://www.ieeetoronto.ca/event/fast-solvers-for-electromagnetics-based-analysis-and-design-of-integrated-circuits-and-systems/
LOCATION:Virtual: https://events.vtools.ieee.org/m/303190
CATEGORIES:Electromagnetics & Radiation
ORGANIZER;CN="Costas Sarris":MAILTO:costas.sarris@utoronto.ca
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220219T100000
DTEND;TZID=America/New_York:20220220T170000
DTSTAMP:20260417T052654
CREATED:20220131T175903Z
LAST-MODIFIED:20220219T160258Z
UID:10000499-1645264800-1645376400@www.ieeetoronto.ca
SUMMARY:MakeUofT 2022
DESCRIPTION:Apply to Canada’s Largest Makeathon by February 5th @11:59pm EST! \n\nTake part in Canada’s Largest Makeathon and transform your ideas into reality! \nHappening online February 19th-20th\, and open to all university students! Your team of 2-4 will have 24h to design and build a project from scratch that integrates hardware and software. We are providing $150 hardware reimbursements to all teams that demo! This year\, the themes for MakeUofT are: wearables\, transport & travel\, and useless inventions! \nOur online makeathon is designed for everyone to participate\, from beginners to experts. To help facilitate your learning experience\, we will have mentors available throughout the event to assist you! You will also be able to interact with some of the top companies in the industry through our networking booths. \nApply at makeuoft.ca by February 5th @11:59pm EST!
URL:https://www.ieeetoronto.ca/event/makeuoft-2022/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/302181
ORGANIZER;CN="University of Toronto IEEE Student Branch":MAILTO:ieeeutstudentbranch@gmail.com
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220210T173000
DTEND;TZID=America/New_York:20220210T190000
DTSTAMP:20260417T052654
CREATED:20220209T161218Z
LAST-MODIFIED:20220210T143726Z
UID:10000500-1644514200-1644519600@www.ieeetoronto.ca
SUMMARY:Design Reliability & Safety for Light Rail Transit (LRT) Propulsion System
DESCRIPTION:Reliability is a main design prerequisite in public transportation systems. This talk will address the governing parameters for a successful reliable propulsion system. Also\, the system is not only required to be reliable but most importantly safe. Those considerations will highlight the power electronics’ components design. The talk will address how to combine safety and reliability into the design phase of any propulsion system. A case study will present the propulsion design of the Light Rail Transit (LRT) Vehicles. All pertaining design requirements will be verified towards the welfare of a successful deployment of the LRT project in Toronto. \nSpeaker(s): James Li \nBiography: James Li is a RAMS Lead in Parsons Inc. He has 30 years of experiences in the Railway and Public Transit industry. Prior to joining Parsons\, James has worked for Bombardier for 15 years as a Lead RAMS Engineer for development of Monorail and Advance Rapid Transit (ART) system. He is a Professional Engineer for the PEO and APEGA\, and ASQ Certified Reliability Engineer. He earned B. Eng from Jilin Polytechnic University and M. Eng from Beijing Jiaotong University in China. \nAgenda:\n1- Introduction of Mr. Li to the audience;\n2- Talk by Mr. Li;\n3- Open discussion;\n4- Conclusions and Adjournment. \nRegister: https://events.vtools.ieee.org/m/303184
URL:https://www.ieeetoronto.ca/event/design-reliability-safety-for-light-rail-transit-lrt-propulsion-system/
LOCATION:Virtual: https://events.vtools.ieee.org/m/303184
CATEGORIES:Power Electronics
ORGANIZER;CN="Mohamed Youssef":MAILTO:mohamed.youssef@uoit.ca
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/New_York:20220207T160000
DTEND;TZID=America/New_York:20220207T170000
DTSTAMP:20260417T052654
CREATED:20220131T175622Z
LAST-MODIFIED:20220207T141804Z
UID:10000498-1644249600-1644253200@www.ieeetoronto.ca
SUMMARY:Practical Antenna Solutions Enabled by Soft and Hard EM Surfaces and Metasurfaces by Prof. Erik Lier
DESCRIPTION:Please join us for an upcoming talk on Feb 07\, 4-5 pm (Eastern Time) by Prof. Erik Lier titled “Practical Antenna Solutions Enabled by Soft and Hard EM Surfaces and Metasurfaces”\, as part of the 2021-2022 IEEE AP-S seminar series. \nAbstract: The presentation will describe how the concept of electromagnetically soft and hard surfaces and later metamaterial horns (metahorns) came about. The talk will also discuss practical antenna solutions enabled by these EM techniques\, as well as future opportunities and challenges in antenna and RF designs. \nAbout Speaker: Dr. Erik Lier received his M.Sc. and Ph.D. from the Norwegian University of Science and Technology\, Trondheim\, Norway. He started working as a university scientific assistant and later as a research scientist at the Electronics Laboratory (ELAB/SINTEF) at the university\, carrying out national and international research on microwave antennas and feed components for the European Space Agency (ESA)\, INTELSAT\, INMARSAT and other satellite organizations and radar companies. He spent a year at UCLA as a visiting scholar studying phased array antenna technology. He co-invented the concept of “Soft and Hard electromagnetic surfaces” which is related to the field of electromagnetic bandgap (EBG) structures and complex surfaces. Since 1990 he has been with Lockheed Martin Space\, where he has been involved in developing new spacecraft antenna and payload technology. He was instrumental in building up shaped reflector capability in the company which resulted in winning the Asiasat-2 satellite program. He has been involved in the development and modernization of the GPS satellite payload for over more than 20 years. His main research interest and contribution has been in the field of phased array antennas\, including design\, analysis\, system engineering\, calibration and test. He was the phased array architect for two phased arrays launched into space. He headed up the internal metamaterials research collaboration effort within the company\, which has included university collaboration and has led to several groundbreaking and practical metamaterial-enhanced antennas for space and ground applications. He is granted 37 US patents\, has authored and co-authored over 140 journal and conference papers\, including two papers in the journal Nature\, co-authored one book and authored a book chapter. He received the 2014 IEEE Antennas and Propagation Harold A. Wheeler Applications Prize Paper Award. He is a Lockheed Martin Senior Technical Fellow\, a Life Fellow of IEEE and a Fellow of IET. \nSpeaker(s): Erik Lier \nVirtual: https://events.vtools.ieee.org/m/302402
URL:https://www.ieeetoronto.ca/event/practical-antenna-solutions-enabled-by-soft-and-hard-em-surfaces-and-metasurfaces-by-prof-erik-lier/
LOCATION:Toronto\, Ontario\, Canada\, Virtual: https://events.vtools.ieee.org/m/302402
CATEGORIES:Electromagnetics & Radiation
ORGANIZER;CN="University of Toronto AP-S":MAILTO:pz.naseri@gmail.com
END:VEVENT
END:VCALENDAR